Recent advances in smart phones have made it feasible to provide indoor Location-Based Services; (LBSs) including through, low cost Wireless Local Area Network (WLAN) infrastructures, such as indoor positioning, tracking, navigation, and location-based security. However, due to the complexity of the indoor environment, it is usually difficult to provide a satisfactory level of accuracy in most applications. Thus, one of the key challenges arises: how to design an accurate and real-time indoor positioning system that can be easily deployed on commercially available mobile devices without any hardware installation or modification.
Received Signal Strength (RSS)-based localization algorithms have been extensively studied as an inexpensive solution, for indoor positioning in recent years. Compared with other measurement-based algorithms (e.g. time of-arrival (TOA) or angle-of-arrival (AOA) measurements of ultra-wideband (UWB) signal), RSS can be easily obtained by a WiFi-integrated mobile device, without any additional hardware. Several ESS-based indoor positioning and tracking algorithms have been proposed based on the position information of access points (APs), which may result in labor overheads for the installation of infractures in real applications.
The key challenge for accurate RSS-based positioning comes from the variations of RSS due to the dynamic and unpredictable nature of radio channels, such as shadowing, multipath, interference, the orientation of wireless device, etc.
Also, as is well known GPS still does not provide optimal foundation for indoor LBSs because of signal outages, positional inaccuracies, and other technical problems prevent localization and tracing.
Certain mobile devices (such as those using the ANDROID™ operating system) are configured to enable the localization of the device hut generally based on communication with a central server with which the mobile device checks in intermittently, providing current location information for the mobile device. Many users however are concerned about the privacy implications of their movements being traced by a remote computer. Furthermore, privacy breaches caused by dealings between individuals and web companies have become very public and have heightened concern around possible privacy implications of LBSs in particular. Certain information services, delivered to or using mobile devices may require some exposure of some location information associated with the user of the mobile device, however, this may be acceptable to the user if they were able to regulate this exposure, which prior art technologies do not permit.
Therefore, what is required is a system and method for localization of a mobile device and tracing of a mobile device, that provides effective support for LBSs including in indoor environments. There is a further need for a system and method for localization of a mobile device that enables LBSs, while maintaining privacy or enabling the user of the mobile device to control exposure of location information to remote computers.